Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Differential epipolar constraint in mobile robot egomotion estimation

The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

Experimental Modeling and Control Strategies on an Open Mobile Robot Platform PRIM

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

PRIM an Open Mobile Robot Platform. Motivation, Present and Future Trends

This paper is focused on the robot mobile platform PRIM (platform robot information multimedia). This robot has been made in order to cover two main needs of our group, on one hand the need for a full open mobile robotic platform that is very useful in fulfilling the teaching and research activity of our school community, and on the other hand with the idea of introducing an ethical product which would be useful as mobile multimedia information point as a service tool. This paper introduces exactly how the system is made up and explains just what the philosophy is behind this work. The navigation strategies and sensor fusion, where machine vision system is the most important one, are oriented towards goal achievement and are the key to the behaviour of the robot

Knowledge integration within an applied mobile robot summer course

This paper presents the use of a mobile robot platform as an innovative educational tool in order to promote and integrate different curriculum knowledge. Hence, it is presented the acquired experience within a summer course named ldquoapplied mobile roboticsrdquo. The main aim of the course is to integrate different subjects as electronics, programming, architecture, perception systems, communications, control and trajectory planning by using the educational open mobile robot platform PRIM. The summer course is addressed to a wide range of student profiles. However, it is of special interests to the students of electrical and computer engineering around their final academic year. The summer course consists of the theoretical and laboratory sessions, related to the following topics: design & programming of electronic devices, modelling and control systems, trajectory planning and control, and computer vision systems. Therefore, the clues for achieving a renewed path of progress in robotics are the integration of several knowledgeable fields, such as computing, communications, and control sciences, in order to perform a higher level reasoning and use decision tools with strong theoretical base

Predictive motion control of a mirosot mobile robot

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model

Integració d’ una unitat inercial i d’ un giroscopi de fibra òptica en un robot submarí i desenvolupament d’ un sistema de posicionament dins una piscina

El Grup de Visió per Computador i Robòtica (VICOROB) del departament d'Electrònica, Informàtica i Automàtica de la Universitat de Girona investiga en el camp de la robòtica submarina. Al CIRS (Centre d’Investigació en Robòtica Submarina), laboratori que forma part del grup VICOROB, el robot submarí Ictineu és la principal eina utilitzada per a desenvolupar els projectes de recerca. Recentment, el CIRS ha adquirit un nou sistema de sensors d' orientació basat en una unitat inercial i un giroscopi de fibra òptica. Aquest projecte pretén realitzar un estudi d' aquests dispositius i integrar-los al robot Ictineu. D' altra banda, aprofitant les característiques d’aquests sensors giroscopics i les mesures d' un sonar ja integrat al robot, es vol desenvolupar un sistema de localització capaç de determinar la posició del robot en el pla horitzontal de la piscina en temps real

Millora experimental de les lleis de control predictiu aplicades sobre la plataforma PRIM I, per el seguiment de trajectòries

Aquest projecte s’aplica sobre el robot PRIM (Plataforma Robotitzada d’Informació Multimèdia), un robot autònom no humanoide creat el 2004 per Ateneu Informàtic (AI) que permet realitzar trajectòries 2D gràcies a un sistema de tracció format per dues rodes motrius propulsades independentment. La plataforma PRIM és controlada a partir del control predictiu, aquest control es va implementar en un projecte anterior, creat per l’Alexandre Blasco Gutierrez i titulat “Implementació de tècniques MPC (Model Predictiu Control) sobre la plataforma PRIM I”. El que es pretén en aquest projecte és millorar els resultats obtinguts en el passat projecte reformulant la llei de control i analitzar les discrepàncies obtingudes en les metodologies que s’utilitzen per minimitzar la funció de costos a partir de simulacions de trajectòries

Integració i estudi d’un conjunt de propulsors per un robot submarí

L’objectiu d’aquest projecte/treball fi de carrera es estudiar els propulsors i el seu protocol de comunicació proporcionant informació útil a l’hora de dissenyar i construir el robot subaquàtic que implementi els propulsors

Odometria i planificació de trajectòries amb el robot e-puck

En el laboratori docent de robòtica s'utilitzen robots mòbils autònoms per treballar aspectes relacionats amb el posicionament, el control de trajectòries, la construcció de mapes... Es disposa de cinc robots comercials anomenats “e-puck”, que es caracteritzen per les seves dimensions reduïdes, dos motors i un conjunt complet de sensors. Aquests robots es programen en C++ utilitzant el simulador Webots, que disposa d'un conjunt de llibreries per programar el robot. També es disposa d'un entorn de proves on els robots es poden moure i evitar obstacles. Donat el poc temps que disposen els estudiants que realitzen pràctiques en aquest laboratori, és d'interès desenvolupar un software que contingui ja el posicionament del robot mitjançant odometria i també varis algoritmes de control de trajectòries. Per últim, en el laboratori es disposa de càmeres i targes d'adquisició de dades. Així doncs els objectius que s'han proposat per el projecte són: 1. Estudi de la documentació i software proporcinats pels fabricants del robot i de l'entorn Webots; 2. Programació del software de l'odometria i realització de proves per comprovar-ne la precisió; 3. Disseny, programació i verificació del software dels algoritmes de planificació de trajectòries. Realització d'experiments per a comprovar-ne el funcionament i 4. Disseny, programació i verificació d'un sistema de visió artificial que permeti conèixer la posició absoluta del robot en l'entorn

Programació del robot e-puck amb Microsoft Robotics Studio

Microsoft Robotics Studio (MRS) és un entorn per a crear aplicacions per a robots utilitzant una gran varietat de plataformes hardware. Conté un entorn de simulació en el que es pot modelar i simular el moviment del robot. Permet també programar el robot, i executar-lo en l’entorn simulat o bé en el real. MRS resol la comunicació entre els diferents processos asíncrons que solen estar presents en el software de control d’un robot: processos per atendre sensors, actuadors, sistemes de control, comunicacions amb l’exterior,... MRS es pot utilitzar per modelar nous robots utilitzant components que ja estiguin disponibles en les seves llibreries, o també permet crear component nous. Per tal de conèixer en detall aquesta eina, seria interessant utilitzar-la per programa els robots e-pucks, uns robots mòbils autònoms de petites dimensions que disposen de dos motors i un complet conjunt de sensors. El que es vol és simular-los, realitzar un programa de control, realitzar la interfície amb el robot i comprovar el funcionament amb el robot real

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Vision-based localization of an underwater robot in a structured environment

This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system